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Search results for: IN SILICO METABOLISM PREDICTION
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Mobilenet-V2 Enhanced Parkinson's Disease Prediction with Hybrid Data Integration
PublicationThis study investigates the role of deep learning models, particularly MobileNet-v2, in Parkinson's Disease (PD) detection through handwriting spiral analysis. Handwriting difficulties often signal early signs of PD, necessitating early detection tools due to potential impacts on patients' work capacities. The study utilizes a three-fold approach, including data augmentation, algorithm development for simulated PD image datasets,...
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CORPORATE BANKRUPTCY PREDICTION IN POLAND AGAINST THE BACKGROUND OF FOREIGN EXPERIENCE
PublicationIn highly developed countries, research in the field of bankruptcy risk prediction has been conducted for many years. For example, in the United States, which can be considered a pioneering country, the first publications appeared in the early twentieth century. In Poland, due to political and economic reasons, the interest in this issue dates back to the early 1990s. For this reason, this publication attempts to answer the following...
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CORPORATE BANKRUPTCY PREDICTION IN POLAND AGAINST THE BACKGROUND OF FOREIGN EXPERIENCE
PublicationIn highly developed countries, research in the field of bankruptcy risk prediction has been conducted for many years. For example, in the United States, which can be considered a pioneering country, the first publications appeared in the early twentieth century. In Poland, due to political and economic reasons, the interest in this issue dates back to the early 1990s. For this reason, this publication attempts to answer the following...
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Numerical Estimation of Hull Hydrodynamic Derivatives in Ship Maneuvering Prediction
PublicationPrediction of the maneuvering characteristics of the ship at the design stage can be done by means of model tests, computational simulations or a combination of both. The model tests can be realized as direct simulation of the standard maneuvers with the free running model, which gives the most accurate results, but is also the least affordable as it requires very large tank or natural lake, as well as complex equipment of the...
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublicationThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Electricity demand prediction by multi-agent system with history-based weighting
PublicationEnergy and load demand forecasting in short-horizons, over an interval ranging from one hour to one week, is crucial for on-line scheduling and security functions of power system. Many load forecasting methods have been developed in recent years which are usually complex solutions with many adjustable parameters. Best-matching models and their relevant parameters have to be determined in a search procedure. We propose a hybrid...
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Evaluation of the prediction ability of air pollutants based on the electronic nose responses
PublicationElectronic noses are able to perform on-line measurements of the toxic volatile compounds in air. Due to their low cost and compact size they can be placed in the areas exposed to pollution, outside the laboratory. Those advantages, on the other side, force the need for development of the reliable sensors data analysis procedures. One of the most important issues connected with electronic noses is the lack of stability of the gas...
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Indole-Acrylonitrile Derivatives as Potential Antitumor and Antimicrobial Agents—Synthesis, In Vitro and In Silico Studies
PublicationA series of 2-(1H-indol-2-yl)-3-acrylonitrile derivatives, 2a–x, 3, 4a–b, 5a–d, 6a–b, and 7, were synthesized as potential antitumor and antimicrobial agents. The structures of the prepared compounds were evaluated based on elemental analysis, IR, 1H- and 13NMR, as well as MS spectra. X-ray crystal analysis of the representative 2-(1H-indol-2-yl)-3-acrylonitrile 2l showed that the acrylonitrile double bond was Z-configured. All...
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Antiproliferative, Antiangiogenic, and Antimetastatic Therapy Response by Mangiferin in a Syngeneic Immunocompetent Colorectal Cancer Mouse Model Involves Changes in Mitochondrial Energy Metabolism
PublicationIn spite of the current advances and achievements in cancer treatments, colorectal cancer (CRC) persists as one of the most prevalent and deadly tumor types in both men and women worldwide. Drug resistance, adverse side effects and high rate of angiogenesis, metastasis and tumor relapse remain one of the greatest challenges in long-term management of CRC and urges need for new leads of anticancer drugs. We demonstrate that CRC...
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Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment
PublicationWe present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7 large assemblies. On average 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups...
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Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublicationIn this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.
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Glucose metabolism disorders in patients with non-functioning adrenal adenomas — single-centre experience
PublicationIntroduction: The presence of glucose metabolism disorders and their possible correlation with degree of cortisol secretion were evaluated in patients with non-functioning adrenal incidentalomas (NFAIs). Material and methods: The study group consisted of 131 patients with hormonally inactive adrenal incidentalomas....
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublicationBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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In silico approaches for better understanding cysteine cathepsin-glycosaminoglycan interactions
PublicationCysteine cathepsins constitute the largest cathepsin family, with 11 proteases in human that are present primarily within acidic endosomal and lysosomal compartments. They are involved in the turnover of intracellular and extracellular proteins. They are synthesized as inactive procathepsins that are converted to mature active forms. Cathepsins play important roles in physiological and pathological processes and, therefore, receive...
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METHOD FOR SHIP'S ROLLING PERIOD PREDICTION WITH REGARD TO NON-LINEARITY OF GZ CURVE
PublicationThe paper deals with the problem of prediction of the rolling period. A special emphasis is put on the practical application of the new method for rolling period prediction with regard to non-linearity of the GZ curve. The one degree-of-freedom rolling equation is applied with using the non-linear stiffness moment and linear damping moment formulas. A number of ships are considered to research the discrepancies between the pending...
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NUMERICAL ESTIMATION OF HULL HYDRODYNAMIC DERIVATIVES IN SHIP MANOUVERING PREDICTION
PublicationOperating in crowded waterways pose a risk of accidents and disasters due to maneuvering limitations of the ship. In order to predict ship’s maneuvering characteristics at the design stage, model tests are often executed as the most accurate prediction tool. Two approaches can be distinguished here: free running model tests and numerical simulations based on planar motion model with the use of hydrodynamic derivatives obtained...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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Personal bankruptcy prediction using machine learning techniques
PublicationIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...
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Cell Metabolism
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Molecular Metabolism
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Endocrinology and Metabolism
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Cancer & Metabolism
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Heart and Metabolism
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Obesity and Metabolism
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Nutrition & Metabolism
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Nature Metabolism
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ColorNephroNet: Kidney tumor malignancy prediction using medical image colorization
PublicationRenal tumor malignancy classification is one of the crucial tasks in urology, being a primary factor included in the decision of whether to perform kidney removal surgery (nephrectomy) or not. Currently, tumor malignancy prediction is determined by the radiological diagnosis based on computed tomography (CT) images. However, it is estimated that up to 16% of nephrectomies could have been avoided because the tumor that had been...
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Caffeine Inhibits Differentiation Of Lung Cancer Stem Cells By Modulating Their Respiratory Metabolism
PublicationIt is ell established that many tumor types contain a fraction of cells, with stem cell-like properties, called cancer stem cells (CSCs), that are resistant to apoptosis induced by therapeutic agents. The presence of CSCs may explain why a standard anticancer treatment, that eliminates only differentiated cancer cells, does not lead to cancer cure.We previously showed the existence of caffeine-sensitive mechanism that controls...
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Prediction of Processor Utilization for Real-Time Multimedia Stream Processing Tasks
PublicationUtilization of MPUs in a computing cluster node for multimedia stream processing is considered. Non-linear increase of processor utilization is described and a related class of algorithms for multimedia real-time processing tasks is defined. For such conditions, experiments measuring the processor utilization and output data loss were proposed and their results presented. A new formula for prediction of utilization was proposed...
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Algorithms for Ship Movement Prediction for Location Data Compression
PublicationDue to safety reasons, the movement of ships on the sea, especially near the coast should be tracked, recorded and stored. However, the amount of vessels which trajectories should be tracked by authorized institutions, often in real time, is usually huge. What is more, many sources of vessels position data (radars, AIS) produces thousands of records describing route of each tracked object, but lots of that records are correlated...
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Rhamnolipid CMC Prediction
PublicationRelationships between the purity, pH, hydrophobicity (log Kow) of the carbon substrate, and the critical micelle concentration (CMC) of rhamnolipid type biosurfactants (RL) were investigated using a quantitative structure–property relationship (QSPR) approach and are presented here for the first time. Measured and literature CMC values of 97 RLs, representing biosurfactants at different stages of purification, were considered....
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Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud
PublicationThe paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Vibro piles performance prediction using result of CPT
PublicationVibro piles belong to the group of full displacement piles with an expanded base, characterised by a very high load capacity, especially in non-cohesive soils. The problem is to adopt a reliable method for the determination of full load–settlement (Q–s) curve. A frequent difficulty is the determination of the load capacity limit based on the static load test because the course of the load–settlement curve is of a linear nature....
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A CNN based coronavirus disease prediction system for chest X-rays
PublicationCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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Color prediction from first principle quantum chemistry computations: a case of alizarin dissolved in methanol
PublicationThe electronic spectrum of alizarin (AZ) in methanol solution was measured and used as reference data for color prediction. The visible part of the spectrum was modelled by different DFT functionals within the TD-DFT framework. The results of a broad range of functionals applied for theoretical spectrum prediction were compared against experimental data by a direct color comparison. The tristimulus model of color expressed in terms...
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Shales Leaching Modelling for Prediction of Flowback Fluid Composition
PublicationThe object of the paper is the prediction of flowback fluid composition at a laboratory scale, for which a new approach is described. The authors define leaching as a flowback fluid generation related to the shale processing. In the first step shale rock was characterized using X-ray fluorescence spectroscopy, X-ray diractometry and laboratory analysis. It was proven that shale rock samples taken from the selected sections of horizontal...
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Diminshed toxicity of C-1748, 4-methyl-9-hydroxyethylamino-1-nitroacridine, compared with its demethyl analog, C-857, corresponds to its resistance to metabolism in HepG2 cells
PublicationThe narrow "therapeutic window" of anti-tumour therapy may be the result of drug metabolism leading to the activation or detoxification of antitumour agents. The aim of this work is to examine (i) whether the diminished toxicity of a potent antitumour drug, C-1748, 9-(2'-hydroxyethylamino)-4-methyl-1-nitroacridine, compared with its 4-demethyl analogue, C-857, results from the differences between the metabolic pathways for the...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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Integrating conventional nitrogen removal with anammox in wastewater treatment systems: Microbial metabolism, sustainability and challenges
PublicationThe various forms of nitrogen (N), including ammonium (NH4+), nitrite (NO2−), and nitrate (NO3−), present in wastewaters can create critical biotic stress and can lead to hazardous phenomena that cause imbalances in biological diversity. Thus, biological nitrogen removal (BNR) from wastewaters is considered to be imperatively urgent. Therefore, anammox-based systems, i.e. partial nitrification and anaerobic ammonium oxidation (PN/anammox)...
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublicationIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublicationIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Agomelatine's antiglycoxidative action—In vitro and in silico research and systematic literature review
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Porcine myofibrillar proteins as potential precursors of bioactive peptides – an in silico study
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Parametric imaging in dynamic glucose metabolism studies in brain
PublicationArtykuł analizuje badania dynamiczne 18FDG-PET, które służą do estymacji metabolizmu glukozy w mózgu. Zbadano w nim wpływ zakłóceń na wyznaczanie interesującego nas parametru LCMRGlc.
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Melatonin: A Cutaneous Perspective on its Production, Metabolism, and Functions
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Pathways and products for the metabolism of vitamin D3 by cytochrome P450scc
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Peroxidative metabolism of arachidonic acid in the course of Lyme arthritis
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